Identifying Customer Needs from User-Generated Content

by Artem Timoshenko
and John R Hauser
| The Social Science Research Network (SSRN)

Big Data

Big Data

Big Data

Big Data

In this article, Timoshenko and Hauser explore how machine learning can be used to identify a rich set of customer needs from user generated content (UGC). Specifically, they detail how customer needs identified using their innovative machine learning algorithm are comparable to those identified through traditional research methods. They discuss how, when UGC is readily available, the machine learning process requires substantially less time, effort and expense than standard research methods.